PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Linear Models”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19Linked to original sources
PubMed1979

Log-linear models in the analysis of disease prevalence data from survival/sacrifice experiments.

This paper considers the problem of analyzing disease prevalence data from survival experiments in which there may also be some serial sacrifice. The assumptions needed for "standard" analyses are reviewed in the context of a general model recently proposed by the authors. This model is then reparametrized in log-linear form, and a generalized EM algorithm is utilized to obtain maximum likelihood estimates of the parameters for a broad class of unsaturated models. Tests based on the relative likelihood are proposed to investigate the effects of treatment, time, and the presence of other diseases on the prevalences and lethalities of specific diseases of interest. An example is given, using data from a large experiment to investigate the effects of low-level radiation on laboratory mice. Finally, some possible directions for future research are indicated.

Animals↗
PubMed1995

A linear modelling approach to automatic interpretation of quality control measurements in mammography.

An approach to the automated interpretation of quality control data is described in which the relationship between small changes in system performance and the resulting small changes in the measured quality control test results are approximated as a set of linear equations in matrix form. The inverse of this forward matrix is then used to identify causal changes from the set of measured changes. This approach has been investigated for the case of mammographic screening quality assurance and shown to provide a potentially useful tool to assist in the interpretation task.

Autoanalysis↗
PubMed2006

Learning nonlinear image manifolds by global alignment of local linear models.

Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. In many applications, the number of degrees of freedom (DOF) in the image generating process is much lower than the number of pixels in the image. If there is a smooth function that maps the DOF to the pixel values, then the images are confined to a low-dimensional manifold embedded in the image space. We propose a method based on probabilistic mixtures of factor analyzers to (1) model the density of images sampled from such manifolds and (2) recover global parameterizations of the manifold. A globally nonlinear probabilistic two-way mapping between coordinates on the manifold and images is obtained by combining several, locally valid, linear mappings. We propose a parameter estimation scheme that improves upon an existing scheme and experimentally compare the presented approach to self-organizing maps, generative topographic mapping, and mixtures of factor analyzers. In addition, we show that the approach also applies to finding mappings between different embeddings of the same manifold.

Algorithms↗
PubMed2004

Linear model of colon cancer initiation.

Cancer results if regulatory mechanisms of cell birth and death are disrupted. Colorectal tumorigenesis is initiated by somatic or inherited mutations in the APC tumor suppressor gene pathway. Several additional genetic hits in other tumor suppressor genes and oncogenes drive the progression from polyps to malignant, invasive cancer. The majority of colorectal cancers present chromosomal instability, CIN, which is caused by mutations in genes that are required to maintain chromosomal stability. A major question in cancer genetics is whether CIN is an early event and thus a driving force of tumor progression. We present a new mathematical model of colon cancer initiation assuming a linear flow from stem cells to differentiated cells to apoptosis. We study the consequences of mutations in different cell types and calculate the conditions for CIN to precede APC inactivation. We find that early emergence of CIN is very likely in colorectal tumorigenesis.

Cell Transformation, Neoplastic↗
PubMed2001

Temporal autocorrelation in univariate linear modeling of FMRI data.

In functional magnetic resonance imaging statistical analysis there are problems with accounting for temporal autocorrelations when assessing change within voxels. Techniques to date have utilized temporal filtering strategies to either shape these autocorrelations or remove them. Shaping, or "coloring," attempts to negate the effects of not accurately knowing the intrinsic autocorrelations by imposing known autocorrelation via temporal filtering. Removing the autocorrelation, or "prewhitening," gives the best linear unbiased estimator, assuming that the autocorrelation is accurately known. For single-event designs, the efficiency of the estimator is considerably higher for prewhitening compared with coloring. However, it has been suggested that sufficiently accurate estimates of the autocorrelation are currently not available to give prewhitening acceptable bias. To overcome this, we consider different ways to estimate the autocorrelation for use in prewhitening. After high-pass filtering is performed, a Tukey taper (set to smooth the spectral density more than would normally be used in spectral density estimation) performs best. Importantly, estimation is further improved by using nonlinear spatial filtering to smooth the estimated autocorrelation, but only within tissue type. Using this approach when prewhitening reduced bias to close to zero at probability levels as low as 1 x 10(-5).

Artifacts↗
PubMed2004

Faster cyclic loess: normalizing RNA arrays via linear models.

MOTIVATION: Our goal was to develop a normalization technique that yields results similar to cyclic loess normalization and with speed comparable to quantile normalization. RESULTS: Fastlo yields normalized values similar to cyclic loess and quantile normalization and is fast; it is at least an order of magnitude faster than cyclic loess and approaches the speed of quantile normalization. Furthermore, fastlo is more versatile than both cyclic loess and quantile normalization because it is model-based. AVAILABILITY: The Splus/R function for fastlo normalization is available from the authors.

Algorithms↗
PubMed2003

Mixtures of general linear models for functional neuroimaging.

We set out a new general framework for making inferences from neuroimaging data, which includes a standard approach to neuroimaging analysis, statistical parametric mapping (SPM), as a special case. The model offers numerous conceptual and statistical advantages that derive from analyzing data at the "cluster level" rather than the "voxel level" and from explicit modeling of the shape and position of clusters of activation. This provides a natural and principled way to pool data from nearby voxels for parameter and variance-component estimation. The model can also be viewed as performing a spatio-temporal cluster analysis. The parameters of the model are estimated using an expectation maximization (EM) algorithm.

Acoustic Stimulation↗
PubMed2000

Polynomial neural network for linear and non-linear model selection in quantitative-structure activity relationship studies on the internet.

This article presents a self-organising multilayered iterative algorithm that provides linear and non-linear polynomial regression models thus allowing the user to control the number and the power of the terms in the models. The accuracy of the algorithm is compared to the partial least squares (PLS) algorithm using fourteen data sets in quantitative-structure activity relationship studies. The calculated data show that the proposed method is able to select simple models characterized by a high prediction ability and thus provides a considerable interest in quantitative-structure activity relationship studies. The software is developed using client-server protocol (Java and C++ languages) and is available for world-wide users on the Web site of the authors.

Internet↗
PubMedDate not supplied

Predicting metabolic control in diabetes: a pilot study using meta-analysis to estimate a linear model.

The purpose of this pilot study was to determine the feasibility of using data from replicated descriptive studies to test a four-variable model designed to explain metabolic control in diabetes. Predictors of metabolic control selected for this analysis were knowledge; health beliefs (and the subscales of barriers, commitment, cues, expectancies, impact on lifestyle, support, and susceptibility); and compliance/adherence. A total of 17 studies, published between 1982 and 1991, were located that met inclusion criteria. Findings indicated that health beliefs have direct and indirect effects on diabetes metabolic control, depending on the individual health belief subscale analyzed. For example, commitment to the benefits of therapy was found to have a statistically significant direct effect on metabolic control; barriers had a statistically significant indirect effect through compliance. The effects of knowledge were consistent throughout the five path models explored. An inverse direct effect was noted on metabolic control and a positive indirect effect was noted on metabolic control through compliance.

Attitude to Health↗
PubMed2005

Hierarchical linear modeling of California Verbal Learning Test--Children's Version learning curve characteristics following childhood traumatic head injury.

California Verbal Learning Test-Children's Version (CVLT-C) indices have been shown to be sensitive to the neurocognitive effects of traumatic brain injury (TBI). The effects of TBI on the learning process were examined with a growth curve analysis of CVLT-C raw scores across the 5 learning trials. The sample with history of TBI comprised 86 children, ages 6-16 years, at a mean of 10.0 (SD=19.5) months postinjury; 37.2% had severe injury, 27.9% moderate, and 34.9% mild. The best-fit model for verbal learning was with a quadratic function. Greater TBI severity was associated with lower rate of acquisition and more gradual deceleration in the rate of acquisition. Intelligence test index scores, previously shown to be sensitive to severity of TBI, were positively correlated with rate of acquisition. Results provide evidence that the CVLT-C learning slope is not a simple linear function and further support for specific effects of TBI on verbal learning.

Adolescent↗
PubMed1999

Aalen's linear model for sampled risk set data: a large sample study.

Borgan and Langholz (1997) describe a method for estimating the parameter functions in Aalen's linear hazard regression model from sampled risk set data. Using a counting process formulation and the martingale central limit theorem, we provide a study of the asymptotic distributional properties of the estimator. The results are applied to study the efficiencies of the nested case-control and counter-matched designs relative to a full cohort analysis.

Case-Control Studies↗
PubMed1996

A generalized linear model for analysing receiver operating characteristic curves.

We present a continuation ratio model for analysing ordinal categorical data and we apply the model to the problem of estimating receiver operating characteristic (ROC) curves. We apply the methods to post-prandial capillary blood glucose measurements as a criterion for a potential screening test for diabetes mellitus. One can obtain point estimates of sensitivity and specificity and their associated standard errors at any value along the observed range of post-prandial capillary blood glucose measurements. Also, in comparison to the models for ROCs described by Tosteson and Begg, ROC curves based on the continuation ratio model have the desired features that allow ROCs to be concave but not necessarily symmetric.

Adult↗
PubMed1990

Changes with background in the linear model of the transient visual system.

There is evidence that the transient channel of temporal human vision behaves as a linear filter for small excursions around a steady background level. The linear filter characteristics depend on the background level. From experimentally obtained impulse responses of the transient channel the linear filter can be modelled and parametrized. This has been done for two different background levels. The two sets of estimated parameters at these two levels show a shift in the parameters which can be described by a single multiplication factor. This result was extrapolated to arbitrary background levels by postulating that each change in background level can be described by a multiplication factor. This leads to an assumption on the variation of the parameters of the linear filter of the transient channel with changes in the background level. This assumption is tested by simulating the system for different parameter sets of the linear filter. The simulations give a good agreement with experimental data on threshold-versus-duration curves and de Lange curves. The (minor) quantitative differences in simulations and experimental data can be explained.

Computer Simulation↗
PubMed1994

[Trend analysis in Hodgkin disease mortality in the German Federal Republic 1955-1989: a comparison of log-linear models with descriptive standard methods].

Age-Period-Cohort (APC) models have become a widely accepted method to analyse incidence and mortality rates of cancer or other diseases. In this paper we compare simple descriptive methods such as plotting age-specific rates and standardized rates with regression models in order to investigate mortality rates of Morbus Hodgkin's disease in Germany (West-Germany) between 1955 and 1989. With any of the approaches it can be seen that the mortality of Morbus Hodgkin's disease has been decreasing around 1970. Although APC-models allow some detailed investigation of the separate influence of the age, period and cohort effect, the results are difficult to interpret as there is no unique solution for the parameter estimates (identification problem of APC-models). For the mortality of Morbus Hodgkin's, the result of the APC-modelling shows that the decrease of mortality is overestimated if the cohort effect is not taken into consideration. We therefore conclude that the interpretation of the APC-model should be done in connection with other methods to avoid misinterpretation. The combination of both approaches will lead to a better understanding of the incidence or mortality patterns of cancer.

Adult↗
PubMed1999

[Research on quality of life of stroke patients and linear model of its impact factors].

The present study reviewed the investigation of 278 stroke patients of Changsha city population in 1994. The result showed that patients of stroke might have different quality of life during the process of their illness. Multiple regression model indicated that major factors on the chronic stroke patients were type of stroke, age, home nursing time, labor-losing days, occupations. The study provides reference source for prevention of stroke and improvement of quality of life.

Adult↗
PubMed2000

Prediction of the effect of enzymes on chick performance when added to cereal-based diets: use of a modified log-linear model.

A previous study demonstrated that a log equation could be used to predict the relationship between the amount of a crude enzyme added to a diet and chick performance. The objective of the current study was to determine if a modification of the original equation, in conjunction with a computer program, would overcome some of its limitations. The modified equation was Y = A + B log (CX + 1), where Y is the estimated performance value; A is the intercept that represents the performance without enzyme supplementation; B, the slope of the equation (performance change per log unit of an enzyme in the diet), is a measure of an enzyme efficacy; C is an amplified factor; and X is the amount of enzyme in the diet. The results demonstrated that the new model more accurately predicted chick performance than that of the original equation with correlations (r) between chick performance and amount of different enzymes added to the diet ranging from r = 0.80 to 0.99 (P < 0.05). In addition, the same trends were found when the model was used to assess the efficacy of a given enzyme added to corn-, wheat-, barley-, and rye-based diets or for combinations of two dietary components (rye and wheat). The model proposed in this study provides a new means of assessing the overall efficacy of an enzyme preparation. This model could be routinely used by enzyme and livestock producers to establish the best combination of different cereals and enzymes so as to maximize net returns.

6-Phytase↗